amcheck/amcheck_next: functions for verifying PostgreSQL relation integrity
Current version: 1.5 (
amcheck_next extension/SQL version: 2)
Author: Peter Geoghegan
License: PostgreSQL license
Supported versions: PostgreSQL 9.4 - PostgreSQL 10
Note that Microsoft Windows is supported, but only on point releases that have the necessary workaround for various restrictions on dynamic linking that only exist on that platform. The minimum supported point releases are 9.4.16, 9.5.11, 9.6.7, and 10.2.
amcheck module provides functions that allow you to verify the logical
consistency of the structure of PostgreSQL indexes. If the structure appears
to be valid, no error is raised. Currently, only B-Tree indexes are supported,
although since in practice the majority of PostgreSQL indexes are B-Tree
amcheck is likely to be effective as a general corruption smoke-test
in production PostgreSQL installations.
See Using amcheck effectively for information
about the kinds of real-world problems
amcheck is intended to detect.
amcheck is a contrib extension module that originally appeared in PostgreSQL
externally maintained version of the extension, which is formally named
amcheck_next to avoid conflicts with
contrib/amcheck, provides the same
functionality as PostgreSQL 11's
contrib/amcheck to earlier versions of
It is safe (though generally not useful) to install
amcheck provides functions that specifically verify various invariants in
the structure of the representation of particular indexes. The correctness of
the access method functions behind index scans and other important operations
relies on these invariants always holding. For example, certain functions
verify, among other things, that all B-Tree pages have items in "logical",
sorted order (e.g., for B-Tree indexes on text, index tuples should be in
collated lexical order). If that particular invariant somehow fails to hold,
we can expect binary searches on the affected page to incorrectly guide index
scans, resulting in wrong answers to SQL queries.
Verification is performed using the same procedures as those used by index scans themselves, which may be user-defined operator class code. For example, B-Tree index verification relies on comparisons made with one or more B-Tree support function 1 routines, much like B-Tree index scans rely on the routines to guide the scan to a point in the underlying table; see the PostgreSQL documentation on Index Access Methods and Operator Classes for details of operator class support functions.
It is recommended that
amcheck be installed using prebuilt packages where
Once the Community APT repository is set up, and PostgreSQL has itself been
installed from a community package, installation of
amcheck is generally
a simple matter of installing the package that matches your PostgreSQL version:
sudo aptitude install postgresql-10-amcheck
Once the Community yum repository is set up, and PostgreSQL has itself been
installed from a community package, installation of
amcheck is generally
a simple matter of installing the package that matches your PostgreSQL version:
sudo yum install amcheck_next10
Building from source
Building using PGXS (generic)
The module can be built using the standard PGXS infrastructure. For this to
work, you will need to have the
pg_config program available in your $PATH.
If you are using a packaged PostgreSQL build and have
(and in your OS user's $PATH), the procedure is as follows:
tar xvzf amcheck-1.5.tar.gz cd amcheck-1.5 make make install
Note that just because
pg_config is located in one user's $PATH does not
necessarily make it so for the root user.
Building Debian/Ubuntu packages from source
The Makefile also provides a target for building Debian packages. The target
has a dependency on
the PostgreSQL source package itself (e.g.
The packages can be created and installed from the amcheck directory as follows:
sudo aptitude install debhelper devscripts postgresql-server-dev-all make deb sudo dpkg -i ./build/postgresql-9.4-amcheck_*.deb
Setting up PostgreSQL
Once the module is built and/or installed, it may be created as a PostgreSQL extension:
mydb=# CREATE EXTENSION amcheck_next;
amcheck functions may be used only by superusers.
amcheck_next extension has a simple interface.
of just a few functions that can be used for verification of a named B-Tree
index. Note that currently, no function inspects the structure of the
underlying heap representation (table).
regclass function arguments are used by
amcheck to identify particular
index relations. This allows
amcheck to accept arguments using various
SQL calling conventions:
-- Use string literal regclass input: SELECT bt_index_check('pg_database_oid_index', true); -- Use oid regclass input (both perform equivalent verification): SELECT bt_index_check(2672, false); SELECT bt_index_check(oid, false) FROM pg_class WHERE relname = 'pg_database_oid_index';
See the PostgreSQL documentation on Object identifier types for more information.
bt_index_check(index regclass, heapallindexed boolean DEFAULT false) returns void
bt_index_check tests that its target, a B-Tree index, respects a variety of
invariants. Example usage:
SELECT bt_index_check(index => c.oid, heapallindexed => i.indisunique), c.relname, c.relpages FROM pg_index i JOIN pg_opclass op ON i.indclass = op.oid JOIN pg_am am ON op.opcmethod = am.oid JOIN pg_class c ON i.indexrelid = c.oid JOIN pg_namespace n ON c.relnamespace = n.oid WHERE am.amname = 'btree' AND n.nspname = 'pg_catalog' -- Don't check temp tables, which may be from another session: AND c.relpersistence != 't' -- Function may throw an error when this is omitted: AND c.relkind = 'i' AND i.indisready AND i.indisvalid ORDER BY c.relpages DESC LIMIT 10;
bt_index_check | relname | relpages ----------------+---------------------------------+---------- | pg_depend_reference_index | 43 | pg_depend_depender_index | 40 | pg_proc_proname_args_nsp_index | 31 | pg_description_o_c_o_index | 21 | pg_attribute_relid_attnam_index | 14 | pg_proc_oid_index | 10 | pg_attribute_relid_attnum_index | 9 | pg_amproc_fam_proc_index | 5 | pg_amop_opr_fam_index | 5 | pg_amop_fam_strat_index | 5
This example shows a session that performs verification of catalog indexes.
Verification of the presence of heap tuples as index tuples is requested for
unique indexes only. Since no error is raised, all indexes tested appear to be
logically consistent. Naturally, this query could easily be changed to call
bt_index_check for every index in the database where verification is
AccessShareLock is acquired on the target index and heap
bt_index_check. This lock mode is the same lock mode acquired on
relations by simple
bt_index_check does not verify invariants that span child/parent
relationships, but will verify the presence of all heap tuples as index tuples
within the index when
true. When a routine, lightweight
test for corruption is required in a live production environment, using
bt_index_check often provides the best trade-off between thoroughness of
verification and limiting the impact on application performance and
bt_index_parent_check(index regclass, heapallindexed boolean DEFAULT false) returns void
bt_index_parent_check tests that its target, a B-Tree index, respects a
variety of invariants. Optionally, when the
heapallindexed argument is
true, the function verifies the presence of all heap tuples that should be
found within the index, and that there are no missing downlinks in the index
structure. The checks performed by
bt_index_parent_check are a superset of
the checks performed by
bt_index_check when called with the same options.
bt_index_parent_check can be thought of as a more thorough variant of
bt_index_parent_check also checks
invariants that span parent/child relationships.
follows the general convention of raising an error if it finds a logical
inconsistency or other problem.
ShareLock is required on the target index by
ShareLock is also acquired on the heap relation). These locks prevent
concurrent data modification from
The locks also prevent the underlying relation from being concurrently
VACUUM (and other utility commands). Note that the function
holds locks for as short a duration as possible, so there is no advantage to
verifying each index individually in a series of transactions, unless long
running queries happen to be of particular concern.
bt_index_parent_check's additional verification is more likely to detect
various pathological cases. These cases may involve an incorrectly implemented
B-Tree operator class used by the index that is checked, or, hypothetically,
undiscovered bugs in the underlying B-Tree index access method code. Note that
bt_index_parent_check cannot be called when Hot Standby is enabled (i.e., on
read-only physical replicas), unlike
heapallindexed argument to verification functions is
additional phase of verification is performed against the table associated with
the target index relation. This consists of a "dummy"
operation, which checks for the presence of all would-be new index tuples
against a temporary, in-memory summarizing structure (this is built when needed
during the first, standard phase). The summarizing structure "fingerprints"
every tuple found within the target index. The high level principle behind
heapallindexed verification is that a new index that is equivalent to the
existing, target index must only have entries that can be found in the existing
heapallindexed phase adds significant overhead: verification
will typically take several times longer than it would with only the standard
consistency checking of the target index's structure. However, verification
will still take significantly less time than an actual
CREATE INDEX. There
is no change to the relation-level locks acquired when
verification is performed. The summarizing structure is bound in size by
maintenance_work_mem. In order to ensure that there is no more than a 2%
probability of failure to detect the absence of any particular index tuple,
approximately 2 bytes of memory are needed per index tuple. As less memory is
made available per index tuple, the probability of missing an inconsistency
increases. This is considered an acceptable trade-off, since it limits the
overhead of verification very significantly, while only slightly reducing the
probability of detecting a problem, especially for installations where
verification is treated as a routine maintenance task.
With many databases, even the default
maintenance_work_mem setting of
is sufficient to have less than a 2% probability of overlooking any single
absent or corrupt tuple. This will be the case when there are no indexes with
more than about 30 million distinct index tuples, regardless of the overall
size of any index, the total number of indexes, or anything else. False
positive candidate tuple membership tests within the summarizing structure
occur at random, and are very unlikely to be the same for repeat verification
operations. Furthermore, within a single verification operation, each missing
or malformed index tuple independently has the same chance of being detected.
If there is any inconsistency at all, it isn't particularly likely to be
limited to a single tuple. All of these factors favor accepting a limited per
operation per tuple probability of missing corruption, in order to enable
performing more thorough index to heap verification more frequently (practical
concerns about the overhead of verification are likely to limit the frequency
of verification). In aggregate, the probability of detecting a hardware fault
or software defect actually increases significantly with this strategy in
most real world cases. Moreover, frequent verification allows problems to be
caught earlier on average, which helps to limit the overall impact of
corruption, and often simplifies root cause analysis.
Using amcheck effectively
Causes of corruption
amcheck can be effective at detecting various types of failure modes that
data page checksums will always fail to catch. These include:
- Structural inconsistencies caused by incorrect operator class implementations.
This includes issues caused by the comparison rules of operating system
collations changing. Comparisons of datums of a collatable type like
must be immutable (just as all comparisons used for B-Tree index scans must be
immutable), which implies that operating system collation rules must never
Though rare, updates to operating system collation rules can cause these issues. More commonly, an inconsistency in the collation order between a master server and a standby server is implicated, possibly because the major operating system version in use is inconsistent. Such inconsistencies will generally only arise on standby servers, and so can generally only be detected on standby servers.
If a problem like this arises, it may not affect each individual index that is ordered using an affected collation, simply because indexed values might happen to have the same absolute ordering regardless of the behavioral inconsistency.
- Structural inconsistencies between indexes and the heap relations that are
heapallindexedverification is performed).
There is no cross-checking of indexes against their heap relation during normal operation. Symptoms of heap corruption can be very subtle.
- Corruption caused by hypothetical undiscovered bugs in the underlying PostgreSQL access method code, sort code, or transaction management code.
Automatic verification of the structural integrity of indexes plays a role in
the general testing of new or proposed PostgreSQL features that could plausibly
allow a logical inconsistency to be introduced. Verification of table
structure and associated visibility and transaction status information plays a
similar role. One obvious testing strategy is to call
continuously when running the standard regression tests.
- Filesystem or storage subsystem faults where checksums happen to simply not be enabled.
amcheck examines a page as represented in some shared memory buffer
at the time of verification if there is only a shared buffer hit when accessing
the block. Consequently,
amcheck does not necessarily examine data read from
the filesystem at the time of verification. Note that when checksums are
amcheck may raise an error due to a checksum failure when a corrupt
block is read into a buffer.
- Corruption caused by faulty RAM, and the broader memory subsystem and operating system.
PostgreSQL does not protect against correctable memory errors and it is assumed you will operate using RAM that uses industry standard Error Correcting Codes (ECC) or better protection. However, ECC memory is typically only immune to single-bit errors, and should not be assumed to provide absolute protection against failures that result in memory corruption.
heapallindexed verification is performed, there is generally a greatly
increased chance of detecting single-bit errors, since strict binary equality
is tested, and the indexed attributes within the heap are tested.
The overhead of calling
bt_index_check for every index on a live production
system is roughly comparable to the overhead of vacuuming; like
verification uses a "buffer access strategy", which limits its impact on which
pages are cached within
shared_buffers. A major design goal of
to support routine verification of all indexes on busy production systems.
heapallindexed verification significantly increases the runtime
amcheck routine will ever modify data, and so no pages will ever be
"dirtied", which is not the case with
VACUUM. On the other hand,
may be required to verify a large number of indexes all at once, which is
typically not a behavior that autovacuum exhibits.
accesses every page in each index verified. This behavior is useful in part
because verification may detect a checksum failure, which may have previously
gone undetected only because no process needed data from the corrupt page in
question, including even an autovacuum worker process.
Note also that
bt_index_parent_check access the contents
of indexes in "logical" order, which, in the worst case, implies that all I/O
operations are performed at random positions on the filesystem. In contrast,
VACUUM always removes dead index tuples from B-Tree indexes while accessing
the contents of B-Tree indexes in sequential order.
Acting on information about corruption
No error concerning corruption raised by
amcheck should ever be a false
amcheck raises errors in the event of conditions that, by
definition, should never happen. It seems unlikely that there could ever be a
useful general remediation to problems it detects.
In general, an explanation for the root cause of an invariant violation should
can play a useful role in diagnosing corruption that
amcheck highlights. A
REINDEX may or may not be effective in repairing corruption, depending on the
exact details of how the corruption originated.
amcheck can only prove the presence of corruption; it cannot
prove its absence.